Abstract

Abstract Introduction: Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, high MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of MD are virtually unknown. Methods: Gene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) recruited through mammographic centres and 64 newly diagnosed breast cancer patients. MD percentage was determined using a previously validated, computerized method on scanned mammograms. Unsupervised hierarchical clustering was used to investigate the presence of subgroups of samples within the normal biopsies. Significance analysis of microarrays (SAM) was performed to identify genes associated with MD. Results: Hierarchical clustering of normal biopsies on the basis of the gene expression data split the individuals into two main groups. These were not significantly associated with MD or BMI. SAM identified 24 genes differentially expressed between high and low MD in the healthy women. Several single nucleotide polymorphisms (SNPs) associated with the expression of these 24 genes were identified. Conclusions: Breast biopsies from healthy women show substantial variation in their gene-expression profiles. Twenty-four genes associated with MD and SNPs associated with their expression were identified. Several of these genes have previously been found to be linked to breast biology and oestrogen metabolism. Validation and further analysis of these genes is ongoing. Citation Information: Clin Cancer Res 2010;16(7 Suppl):B43

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